• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.123-128
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• 1998

This paper presents time domain identification of an interval system. We conjectured that Markov parameters (Pulse Responses) from Kharitonov plants would envelope those of the whole interval system. The examination on interrelations between Markov parameters from Kharitonov plants of an interval system and those of the whole interval system determines the validity of the conjecture and is used to give some extremal properties of Markov parameters. The results of this paper are shown in simulations on MBC500 Magnetic Bearing System and a given interval system.

• Smart Structures and Systems
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• 제15권3호
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• International Journal of Reliability and Applications
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• 제6권1호
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• pp.13-29
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• 2005

This paper deals with the stochastic analysis of a three-states semi-Markov reliability model. Using both the maximum likelihood and Bayes procedures, the parameters included in this model are estimated. Next, assuming that the lifetime and repair time are generalized exponential random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is discussed. Finally, some of the obtained results are compared with those available in the literature.

• Industrial Engineering and Management Systems
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• 제15권2호
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• pp.131-142
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• 2016

We consider a multi-server queueing system without buffer and with two types of customers as a model of operation of a mobile network cell. Customers arrive at the system in the marked Markovian arrival flow. The service times of customers are exponentially distributed with parameters depending on the type of customer. A part of the available servers is reserved exclusively for service of first type customers. Customers who do not receive service upon arrival, can make repeated attempts. The system operation is influenced by random factors, leading to a change of the system parameters, including the total number of servers and the number of reserved servers. The behavior of the system is described by the multi-dimensional Markov chain. The generator of this Markov chain is constructed and the ergodicity condition is derived. Formulas for computation of the main performance measures of the system based on the stationary distribution of the Markov chain are derived. Numerical examples are presented.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2522-2524
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• 2005

We need build a mathematical to apply the system theory to real system, phenomenon analysis, prediction, control, simulation and so on. Especially system identification is building a model from input and output data. This study shows q-Markov Cover based system identification. When we do this, in order to make the identification possible under more general conditions with estimation of the system order, Markov parameters and covariance parameters from input and douput data, 1 suggest the way we can get an optimal model by estimating and Identifying of covariance matrix of observation noises repeatedly.

• 한국통신학회논문지
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• 제37권3C호
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• pp.224-232
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• 2012

Priority MAC is an important issue in every communication system when we consider differentiated service applications. In this paper, we propose a mechanism to support priority MAC based on multi-parameters for IEEE 802.15.7 visible light communication (VLC). By using three parameters such as number of backoff times (NB), backoff exponent (BE) and contention window (CW), we provide priority for multi-level differentiated service applications. We consider beacon-enabled VLC personal area network (VPAN) mode with slotted version for random access algorithm in this paper. Based on a discrete-time Markov chain, we analyze the performance of proposed mechanism under non-saturation environments. By building a Markov chain model for multi-parameters, this paper presents the throughput and transmission delay time for VLC system. Numerical results show that we can apply three parameters to control the priority for VLC MAC protocol.

• 시스템엔지니어링학술지
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• 제14권1호
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• pp.44-51
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• 2018

The purpose of RAM analysis in weapon systems is to reduce life cycle costs, along with improving combat readiness by meeting RAM target value. We analyzed the sensitivity of the RAM analysis parameters to the use of the operating system by using the Markov Process based model (MPS, Markov Process Simulation) developed for RAM analysis. A Markov process-based RAM analysis model was developed to analyze the sensitivity of parameters (MTBF, MTTR and ALDT) to the utility of the 81mm mortar. The time required for the application to reach the steady state is about 15,000H, which is about 2 years, and the sensitivity of the parameter is highest for ALDT. In order to improve combat readiness, there is a need for continuous improvement in ALDT.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.335-339
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• 1998

This paper presents a closed loop identification algorithm in time domain. This algorithm can be used for identification of unstable system and for model validation of system which is difficult to derive analytical model. In time domain, projection filter, which projects a finite number of input output data of a system into its current space, is used to relate the state space model with a finite difference model. Then recursive relations between the Markov parameters and the ARX model coefficients are derived to identify the system, controller and Kalman filter Markov parameters recursively, which are finally used to identify the system, controller and Kalman filter gains. The NASA LAMSTF is used to validate the algorithms developed.

• International Journal of Reliability and Applications
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• 제9권2호
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• International Journal of Reliability and Applications
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• 제12권1호
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• pp.1-14
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• 2011

This paper discusses the stochastic analysis and the statistical inference of a quadratic failure rate semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are random variables with quadratic failure rate, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system is derived. Many important special cases are discussed.